Uncertainty in sea level rise projections due to the dependence between contributors

Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion...

Full description

Bibliographic Details
Main Author: Le Bars, Dewi
Format: Report
Language:unknown
Published: EarthArXiv 2018
Subjects:
Online Access:https://dx.doi.org/10.17605/osf.io/uvw3s
https://eartharxiv.org/uvw3s/
_version_ 1821531473717493760
author Le Bars, Dewi
author_facet Le Bars, Dewi
author_sort Le Bars, Dewi
collection DataCite
description Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore the uncertainty of total sea level depends on the correlation between the uncertainties of the contributors. This fact is important to understand the differences in the uncertainty of sea level projections from different methods. Using two process-based models to project sea level for the 21st century, we show how to model the correlation structure and its time dependence. In these models the correlation primarily arises from uncertainty of future global mean surface temperature that correlates with almost all contributors. Assuming that sea level contributors are independent of each other, an assumption made in many sea level projections, underestimates the uncertainty in sea level projections. As a result, high-end low probability events that are important for decision making are underestimated. The uncertainty in the strength of the dependence between contributors is also explored. New dependence relation between the uncertainty of dynamical processes, and surface mass balance in glaciers and ice sheets are introduced in our model. Total sea level uncertainty is found to be as sensitive to the dependence between contributors as to uncertainty in individual contributors like thermal expansion and Greenland ice sheet.
format Report
genre Greenland
Ice Sheet
genre_facet Greenland
Ice Sheet
geographic Greenland
geographic_facet Greenland
id ftdatacite:10.17605/osf.io/uvw3s
institution Open Polar
language unknown
op_collection_id ftdatacite
op_doi https://doi.org/10.17605/osf.io/uvw3s
op_rights CC-By Attribution 4.0 International
publishDate 2018
publisher EarthArXiv
record_format openpolar
spelling ftdatacite:10.17605/osf.io/uvw3s 2025-01-16T22:13:18+00:00 Uncertainty in sea level rise projections due to the dependence between contributors Le Bars, Dewi 2018 https://dx.doi.org/10.17605/osf.io/uvw3s https://eartharxiv.org/uvw3s/ unknown EarthArXiv CC-By Attribution 4.0 International Physical Sciences and Mathematics Statistics and Probability Statistical Models Probability Applied Statistics Oceanography and Atmospheric Sciences and Meteorology Climate Environmental Sciences Earth Sciences Preprint Text article-journal ScholarlyArticle 2018 ftdatacite https://doi.org/10.17605/osf.io/uvw3s 2021-11-05T12:55:41Z Sea level rises at an accelerating pace threatening coastal communities all over the world. In this context sea level projections are key tools to help risk mitigation and adaptation. Sea level projections are often made using models of the main contributors to sea level rise (e.g. thermal expansion, glaciers, ice sheets...). To obtain the total sea level these contributions are added, therefore the uncertainty of total sea level depends on the correlation between the uncertainties of the contributors. This fact is important to understand the differences in the uncertainty of sea level projections from different methods. Using two process-based models to project sea level for the 21st century, we show how to model the correlation structure and its time dependence. In these models the correlation primarily arises from uncertainty of future global mean surface temperature that correlates with almost all contributors. Assuming that sea level contributors are independent of each other, an assumption made in many sea level projections, underestimates the uncertainty in sea level projections. As a result, high-end low probability events that are important for decision making are underestimated. The uncertainty in the strength of the dependence between contributors is also explored. New dependence relation between the uncertainty of dynamical processes, and surface mass balance in glaciers and ice sheets are introduced in our model. Total sea level uncertainty is found to be as sensitive to the dependence between contributors as to uncertainty in individual contributors like thermal expansion and Greenland ice sheet. Report Greenland Ice Sheet DataCite Greenland
spellingShingle Physical Sciences and Mathematics
Statistics and Probability
Statistical Models
Probability
Applied Statistics
Oceanography and Atmospheric Sciences and Meteorology
Climate
Environmental Sciences
Earth Sciences
Le Bars, Dewi
Uncertainty in sea level rise projections due to the dependence between contributors
title Uncertainty in sea level rise projections due to the dependence between contributors
title_full Uncertainty in sea level rise projections due to the dependence between contributors
title_fullStr Uncertainty in sea level rise projections due to the dependence between contributors
title_full_unstemmed Uncertainty in sea level rise projections due to the dependence between contributors
title_short Uncertainty in sea level rise projections due to the dependence between contributors
title_sort uncertainty in sea level rise projections due to the dependence between contributors
topic Physical Sciences and Mathematics
Statistics and Probability
Statistical Models
Probability
Applied Statistics
Oceanography and Atmospheric Sciences and Meteorology
Climate
Environmental Sciences
Earth Sciences
topic_facet Physical Sciences and Mathematics
Statistics and Probability
Statistical Models
Probability
Applied Statistics
Oceanography and Atmospheric Sciences and Meteorology
Climate
Environmental Sciences
Earth Sciences
url https://dx.doi.org/10.17605/osf.io/uvw3s
https://eartharxiv.org/uvw3s/